{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/timeseriesAI/tsai/blob/master/tutorial_nbs/00b_How_to_use_numpy_arrays_in_fastai.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "created by Ignacio Oguiza - email: timeseriesAI@gmail.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to work with numpy arrays in fastai: a time series classification example ⏳ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'd like to share with you how you can work with numpy arrays in **fastai** through a time series classification example. \n",
    "\n",
    "I've used timeseriesAI (based on v1 extensiively). To be able to use fastai v2 I have a few requirements: \n",
    "\n",
    "\n",
    "* Use univariate and multivariate time series\n",
    "* Use labeled (X,y) and unlabeled (X,) datasets\n",
    "* Data may be already split in train/ valid\n",
    "* In-memory and on-disk np.arrays (np.memmap in case of larger than RAM data)\n",
    "* Slice the dataset (based on selected variables and/ or sequence steps)\n",
    "* Use item and batch tfms\n",
    "* Create batch with specified output types (TSTensor, TensorCategory, etc)\n",
    "* Show batch (with tfms)\n",
    "* Show results\n",
    "* Add test data and unlabeled datasets\n",
    "* Export and predict on new data\n",
    "* Equal or better performance than native Pytorch, fastai v1 & vanilla fastai v2\n",
    "\n",
    "These are pretty challanging. Let's see if fastai can meet them (with limited customization)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import libraries 📚"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[K     |████████████████████████████████| 194kB 14.6MB/s \n",
      "\u001b[K     |████████████████████████████████| 22.2MB 45.0MB/s \n",
      "\u001b[K     |████████████████████████████████| 5.7MB 47.7MB/s \n",
      "\u001b[K     |████████████████████████████████| 9.5MB 16.2MB/s \n",
      "\u001b[K     |████████████████████████████████| 3.2MB 42.1MB/s \n",
      "\u001b[K     |████████████████████████████████| 2.5MB 43.2MB/s \n",
      "\u001b[K     |████████████████████████████████| 174kB 54.3MB/s \n",
      "\u001b[K     |████████████████████████████████| 901kB 43.3MB/s \n",
      "\u001b[K     |████████████████████████████████| 92kB 12.4MB/s \n",
      "\u001b[K     |████████████████████████████████| 61kB 9.3MB/s \n",
      "\u001b[K     |████████████████████████████████| 25.3MB 66.3MB/s \n",
      "\u001b[K     |████████████████████████████████| 675kB 47.1MB/s \n",
      "\u001b[K     |████████████████████████████████| 102kB 12.3MB/s \n",
      "\u001b[?25h  Building wheel for tsai (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Building wheel for contextvars (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
     ]
    }
   ],
   "source": [
    "# ## NOTE: UNCOMMENT AND RUN THIS CELL IF YOU NEED TO INSTALL/ UPGRADE TSAI\n",
    "# stable = False # True: stable version in pip, False: latest version from github\n",
    "# if stable: \n",
    "#     !pip install tsai -U >> /dev/null\n",
    "# else:      \n",
    "#     !pip install git+https://github.com/timeseriesAI/tsai.git -U >> /dev/null\n",
    "# ## NOTE: REMEMBER TO RESTART (NOT RECONNECT/ RESET) THE KERNEL/ RUNTIME ONCE THE INSTALLATION IS FINISHED"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/nacho/anaconda3/envs/py36/lib/python3.6/site-packages/numba/core/errors.py:154: UserWarning: Insufficiently recent colorama version found. Numba requires colorama >= 0.3.9\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "os             : Darwin\n",
      "os version     : 19.6.0\n",
      "python         : 3.6.13\n",
      "tsai           : 0.2.20\n",
      "fastai         : 2.5.2\n",
      "fastcore       : 1.3.26\n",
      "torch          : 1.9.0\n",
      "n_cpus         : 8\n",
      "device         : cpu\n"
     ]
    }
   ],
   "source": [
    "from tsai.all import *\n",
    "computer_setup()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data 🔢"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset: StarLightCurves\n",
      "X_train: (1000, 1, 1024)\n",
      "y_train: (1000,)\n",
      "X_valid: (8236, 1, 1024)\n",
      "y_valid: (8236,) \n",
      "\n",
      "Dataset: StarLightCurves\n",
      "X      : (9236, 1, 1024)\n",
      "y      : (9236,)\n",
      "splits : (#1000) [0,1,2,3,4,5,6,7,8,9...] (#8236) [1000,1001,1002,1003,1004,1005,1006,1007,1008,1009...] \n",
      "\n",
      "Dataset: StarLightCurves\n",
      "X      : (9236, 1, 1024)\n",
      "y      : (9236,)\n",
      "splits : (#1000) [0,1,2,3,4,5,6,7,8,9...] (#8236) [1000,1001,1002,1003,1004,1005,1006,1007,1008,1009...] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# dataset id\n",
    "dsid = 'StarLightCurves'\n",
    "X_train, y_train, X_valid, y_valid = get_UCR_data(dsid, parent_dir='./data/UCR/', verbose=True, on_disk=False)\n",
    "X_on_disk, y_on_disk, splits = get_UCR_data(dsid, parent_dir='./data/UCR/', verbose=True, on_disk=True, return_split=False)\n",
    "X_in_memory, y_in_memory, splits = get_UCR_data(dsid, parent_dir='./data/UCR/', verbose=True, on_disk=False, return_split=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bs = 128\n",
    "idx = np.random.randint(len(X_in_memory), size=bs)\n",
    "train_idx = np.random.randint(len(splits[0]), size=bs)\n",
    "valid_idx = np.random.randint(len(splits[1]), size=bs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building blocks: NumpyTensor/ TSTensor 🧱"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since fastai is based on Pytorch, you'll need to somehow transform the numpy arrays to tensors (NumpyTensor or TSTensor for TS). \n",
    "\n",
    "There're transform functions called ToNumpyTensor/ ToTSTensor that transforms an array into a tensor of type NumpyTensor/ TSTensor (both have a show method)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NumpyTensor(shape:(9236, 1, 1024))\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nt = NumpyTensor(X_in_memory)\n",
    "print(nt)\n",
    "nt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TSTensor(samples:9236, vars:1, len:1024)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstensor = TSTensor(X_in_memory)\n",
    "print(tstensor)\n",
    "tstensor[0].show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance benchmarks ⏱"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In fastai v2 there are multiple options to create dataloaders. Let's see some of them and most importantly wheteher they meet our requirements.\n",
    "\n",
    "I will compare performance on 2 processes: \n",
    "\n",
    "- cycle_dl: process to cycle through the entire valid dataset (adapted from a function developed by Thomas Capelle (fastai's @tcapelle))\n",
    "- train model for 25 epochs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pytorch dataloader & NumpyDataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For reference, we'll test performance in the most simple dataset we can have and the native Pytorch dataloader:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[[-0.5697, -0.5679, -0.5659,  ..., -0.5485, -0.5545, -0.5608]],\n",
       " \n",
       "         [[-0.5283, -0.5209, -0.5129,  ..., -0.6006, -0.5799, -0.5563]],\n",
       " \n",
       "         [[ 0.1642,  0.1819,  0.1986,  ...,  0.1773,  0.1694,  0.1617]],\n",
       " \n",
       "         ...,\n",
       " \n",
       "         [[ 0.5924,  0.5822,  0.5737,  ...,  0.6469,  0.6374,  0.6268]],\n",
       " \n",
       "         [[ 0.5427,  0.5495,  0.5557,  ...,  0.4949,  0.4907,  0.4858]],\n",
       " \n",
       "         [[-0.1532, -0.1441, -0.1353,  ..., -0.1930, -0.1855, -0.1781]]]),\n",
       " tensor([2, 3, 3, 1, 2, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 1, 1, 3, 3, 3,\n",
       "         2, 1, 3, 1, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 2, 3, 3, 1, 3, 3, 2, 1, 1, 3,\n",
       "         3, 3, 3, 2, 1, 1, 3, 3, 3, 3, 3, 3, 1, 1, 2, 3, 3, 2, 3, 3, 3, 1, 1, 3,\n",
       "         2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 3, 1, 3, 1, 3,\n",
       "         3, 3, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 2, 1, 3, 3, 1, 3, 3, 2, 3, 2, 3, 3,\n",
       "         3, 3, 3, 3, 2, 3, 3, 1]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid_ds    = TorchDataset(np.array(X_valid), np.array(y_valid).astype(int))\n",
    "valid_dl    = torch.utils.data.DataLoader(valid_ds, batch_size=128)\n",
    "xb, yb = next(iter(valid_dl))\n",
    "xb, yb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 50.4 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(valid_dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 120.84 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "1 loop, best of 3: 67 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl_to_device(valid_dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 loops, best of 3: 193 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit xb.to(default_device()), yb.to(default_device())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is very fast, but:\n",
    "\n",
    "* batch is returned on **cpu** (so additional time is required to pass it to gpu). The challanging benchmark is the one in the cycle_dl_to_device(valid_dl) test.\n",
    "* cannot be easily integrated with fastai.\n",
    "\n",
    "It will be difficult to find a solution that performs at the same level 😅!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want a simple solution that you can use with fastai you will need to use DataLoader (fastai's default dataloader) instead of Pytorch's native dataloader."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TSTensor(samples:128, vars:1, len:1024) TensorCategory([1, 2, 2, 0, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 0, 0, 2, 2, 2,\n",
      "        1, 0, 2, 0, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 0, 2, 2, 1, 0, 0, 2,\n",
      "        2, 2, 2, 1, 0, 0, 2, 2, 2, 2, 2, 2, 0, 0, 1, 2, 2, 1, 2, 2, 2, 0, 0, 2,\n",
      "        1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 2, 2, 0, 2, 0, 2,\n",
      "        2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 0, 2, 2, 0, 2, 2, 1, 2, 1, 2, 2,\n",
      "        2, 2, 2, 2, 1, 2, 2, 0], device='cuda:0')\n",
      "shape: 1000         bs: (128, 1, 1024)\n",
      "1 loop, best of 3: 970 ms per loop\n"
     ]
    }
   ],
   "source": [
    "train_ds = TSDataset(np.array(X_train), np.array(y_train).astype(int) - 1, types=(TSTensor, TensorCategory))\n",
    "train_dl = DataLoader(train_ds, bs=128, num_workers=0)\n",
    "valid_ds = TSDataset(np.array(X_valid), np.array(y_valid).astype(int) - 1, types=(TSTensor, TensorCategory))\n",
    "valid_dl = DataLoader(valid_ds, bs=128, num_workers=0)\n",
    "dls      = DataLoaders(train_dl, valid_dl, device=default_device())\n",
    "xb,yb = next(iter(dls.valid))\n",
    "print(xb, yb)\n",
    "print(f'shape: {str(len(train_ds)):10}   bs: {xb.shape}')\n",
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But this is relatively slow, as DataLoader processes samples one at a time, and each item needs to be casted to the appropriate type.\n",
    "\n",
    "Note: we'll see how this can accelerated later by processing all batch samples at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.885291</td>\n",
       "      <td>1.032657</td>\n",
       "      <td>0.577222</td>\n",
       "      <td>00:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.720518</td>\n",
       "      <td>0.979809</td>\n",
       "      <td>0.577222</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.618322</td>\n",
       "      <td>0.802784</td>\n",
       "      <td>0.749757</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.542511</td>\n",
       "      <td>0.587167</td>\n",
       "      <td>0.845070</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.480236</td>\n",
       "      <td>1.097497</td>\n",
       "      <td>0.420350</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.434654</td>\n",
       "      <td>1.209982</td>\n",
       "      <td>0.371782</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.393970</td>\n",
       "      <td>0.402631</td>\n",
       "      <td>0.944026</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.351953</td>\n",
       "      <td>0.562964</td>\n",
       "      <td>0.757892</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.314740</td>\n",
       "      <td>0.507314</td>\n",
       "      <td>0.855877</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.279365</td>\n",
       "      <td>0.293855</td>\n",
       "      <td>0.867897</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.249008</td>\n",
       "      <td>0.145231</td>\n",
       "      <td>0.959446</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.223245</td>\n",
       "      <td>0.542948</td>\n",
       "      <td>0.732516</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.202113</td>\n",
       "      <td>0.151863</td>\n",
       "      <td>0.962118</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.183818</td>\n",
       "      <td>0.328788</td>\n",
       "      <td>0.862312</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.166897</td>\n",
       "      <td>0.106638</td>\n",
       "      <td>0.976081</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.151818</td>\n",
       "      <td>0.184831</td>\n",
       "      <td>0.939534</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.138475</td>\n",
       "      <td>0.104007</td>\n",
       "      <td>0.972195</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.126374</td>\n",
       "      <td>0.093757</td>\n",
       "      <td>0.975838</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.115607</td>\n",
       "      <td>0.087813</td>\n",
       "      <td>0.978023</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.106101</td>\n",
       "      <td>0.088882</td>\n",
       "      <td>0.975959</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.097709</td>\n",
       "      <td>0.084435</td>\n",
       "      <td>0.977902</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.090382</td>\n",
       "      <td>0.085619</td>\n",
       "      <td>0.976445</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.084027</td>\n",
       "      <td>0.081918</td>\n",
       "      <td>0.977902</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.078572</td>\n",
       "      <td>0.081182</td>\n",
       "      <td>0.978752</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.073935</td>\n",
       "      <td>0.080945</td>\n",
       "      <td>0.978752</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "66.98143315315247\n"
     ]
    }
   ],
   "source": [
    "model = InceptionTime(X_train.shape[-2], dls.c)\n",
    "learn = Learner(dls, model, loss_func=nn.CrossEntropyLoss(), metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fastai v1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For comparison, I've run the same exact test in the same machine with fastai v1 timeseries code and these are the timings: : \n",
    "\n",
    "- cycle_dl:  1.01s\n",
    "- training time: 102 s\n",
    "\n",
    "These are the timings we'd like to beat if we want to have a faster TS framework."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fastai v2:  Factory method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since UCR data was already split into train and test, we'll pass IndexSplitter(splits[1]) as splitter so we get exactly the same split."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:128, vars:1, len:1024), TSTensor(len:128))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dls = TSDataLoaders.from_numpy(X_in_memory, y_in_memory, splitter=IndexSplitter(splits[1]), bs=64, val_bs=128, num_workers=0)\n",
    "next(iter(dls.valid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 668 ms, sys: 2.83 ms, total: 670 ms\n",
      "Wall time: 675 ms\n"
     ]
    }
   ],
   "source": [
    "%time cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5.08 s, sys: 3.13 ms, total: 5.08 s\n",
      "Wall time: 5.08 s\n"
     ]
    }
   ],
   "source": [
    "%time cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.889228</td>\n",
       "      <td>1.096725</td>\n",
       "      <td>0.176178</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.708641</td>\n",
       "      <td>0.706046</td>\n",
       "      <td>0.842035</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.588346</td>\n",
       "      <td>0.438201</td>\n",
       "      <td>0.851991</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.497608</td>\n",
       "      <td>0.336901</td>\n",
       "      <td>0.847742</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.423327</td>\n",
       "      <td>0.335085</td>\n",
       "      <td>0.893152</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.350036</td>\n",
       "      <td>0.728415</td>\n",
       "      <td>0.856727</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.289225</td>\n",
       "      <td>0.169988</td>\n",
       "      <td>0.966731</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.244145</td>\n",
       "      <td>0.214525</td>\n",
       "      <td>0.934070</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.212108</td>\n",
       "      <td>0.361348</td>\n",
       "      <td>0.851627</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.183981</td>\n",
       "      <td>0.136590</td>\n",
       "      <td>0.950461</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.162040</td>\n",
       "      <td>0.127744</td>\n",
       "      <td>0.963696</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.146611</td>\n",
       "      <td>0.652575</td>\n",
       "      <td>0.703983</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.132894</td>\n",
       "      <td>0.092661</td>\n",
       "      <td>0.975716</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.119872</td>\n",
       "      <td>0.123395</td>\n",
       "      <td>0.959446</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.108606</td>\n",
       "      <td>0.081364</td>\n",
       "      <td>0.979966</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.099845</td>\n",
       "      <td>0.087254</td>\n",
       "      <td>0.979723</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.090260</td>\n",
       "      <td>0.092128</td>\n",
       "      <td>0.972438</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.082080</td>\n",
       "      <td>0.104858</td>\n",
       "      <td>0.966003</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.076781</td>\n",
       "      <td>0.097129</td>\n",
       "      <td>0.971467</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.072384</td>\n",
       "      <td>0.082482</td>\n",
       "      <td>0.976081</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.067324</td>\n",
       "      <td>0.074895</td>\n",
       "      <td>0.979237</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.061998</td>\n",
       "      <td>0.075848</td>\n",
       "      <td>0.978995</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.058664</td>\n",
       "      <td>0.074913</td>\n",
       "      <td>0.979359</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.055124</td>\n",
       "      <td>0.073873</td>\n",
       "      <td>0.979237</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.053286</td>\n",
       "      <td>0.073417</td>\n",
       "      <td>0.978995</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "180.95779705047607\n"
     ]
    }
   ],
   "source": [
    "model = InceptionTime(X_in_memory.shape[-2], dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This method is very easy to use, but it's pretty slow."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fastai v2:  Datablock API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: 8236         bs: (128, 1, 1024)\n"
     ]
    }
   ],
   "source": [
    "getters = [ItemGetter(0), ItemGetter(1)]\n",
    "dblock = DataBlock(blocks=(TSTensorBlock, CategoryBlock()),\n",
    "                   getters=getters,\n",
    "                   splitter=IndexSplitter(splits[1]),\n",
    "                   item_tfms=None,\n",
    "                   batch_tfms=None)\n",
    "source = itemify(X_in_memory, y_in_memory)\n",
    "dls = dblock.dataloaders(source, bs=64, val_bs=128, num_workers=0)\n",
    "xb,yb = next(iter(dls.valid))\n",
    "print(f'shape: {str(len(dls.valid.dataset)):10}   bs: {xb.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 682 ms, sys: 4.44 ms, total: 687 ms\n",
      "Wall time: 687 ms\n"
     ]
    }
   ],
   "source": [
    "%time cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 5.21 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So it takes > 3 s to cycle the entire dataloader. This is much slower than Pytorch simple model (although fastai v2 provides a lot more functionality!)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.925692</td>\n",
       "      <td>1.080371</td>\n",
       "      <td>0.237980</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.719025</td>\n",
       "      <td>0.754160</td>\n",
       "      <td>0.840578</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.591005</td>\n",
       "      <td>0.452540</td>\n",
       "      <td>0.851627</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.495703</td>\n",
       "      <td>0.356732</td>\n",
       "      <td>0.849684</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.418577</td>\n",
       "      <td>0.392448</td>\n",
       "      <td>0.863526</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.352573</td>\n",
       "      <td>4.395863</td>\n",
       "      <td>0.279869</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.297641</td>\n",
       "      <td>0.250217</td>\n",
       "      <td>0.870204</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.250921</td>\n",
       "      <td>0.491929</td>\n",
       "      <td>0.854541</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.214137</td>\n",
       "      <td>0.692183</td>\n",
       "      <td>0.696940</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.187864</td>\n",
       "      <td>0.467172</td>\n",
       "      <td>0.856605</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.168275</td>\n",
       "      <td>0.220637</td>\n",
       "      <td>0.899344</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.151706</td>\n",
       "      <td>0.170369</td>\n",
       "      <td>0.938441</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.135140</td>\n",
       "      <td>0.168796</td>\n",
       "      <td>0.935284</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.121308</td>\n",
       "      <td>0.168452</td>\n",
       "      <td>0.937712</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.111701</td>\n",
       "      <td>0.088925</td>\n",
       "      <td>0.978145</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.104952</td>\n",
       "      <td>0.095553</td>\n",
       "      <td>0.978266</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.097710</td>\n",
       "      <td>0.090059</td>\n",
       "      <td>0.975352</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.090380</td>\n",
       "      <td>0.104368</td>\n",
       "      <td>0.970131</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.082278</td>\n",
       "      <td>0.079864</td>\n",
       "      <td>0.978752</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.075697</td>\n",
       "      <td>0.081727</td>\n",
       "      <td>0.976931</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.070388</td>\n",
       "      <td>0.077852</td>\n",
       "      <td>0.979237</td>\n",
       "      <td>00:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.064938</td>\n",
       "      <td>0.078607</td>\n",
       "      <td>0.978145</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.060898</td>\n",
       "      <td>0.077570</td>\n",
       "      <td>0.978630</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.057862</td>\n",
       "      <td>0.076864</td>\n",
       "      <td>0.979359</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.055515</td>\n",
       "      <td>0.075984</td>\n",
       "      <td>0.979359</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "199.93124127388\n"
     ]
    }
   ],
   "source": [
    "model = InceptionTime(X_in_memory.shape[-2], dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is very slow compared to the native Pytorch, and even to fastai v1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mixed Pytorch dataset + Fastai DataLoaders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "Sylvain Gugger provided an alternative recommendation to use numpy arrays in this [post](https://forums.fast.ai/t/datablock-with-numpy-input/64848/2):\n",
    "\n",
    "\"You can create a DataLoaders object from regular PyTorch datasets (though all the visualization methods like show_batch and show_results will fail).\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: 8236         bs: torch.Size([128, 1, 1024])\n"
     ]
    }
   ],
   "source": [
    "train_ds = TorchDataset(np.array(X_train), np.array(y_train).astype(int) - 1)\n",
    "valid_ds = TorchDataset(np.array(X_valid), np.array(y_valid).astype(int) - 1)\n",
    "dls = DataLoaders.from_dsets(train_ds, valid_ds, batch_size=128, num_workers=0, device=default_device())\n",
    "xb,yb = next(iter(dls.valid))\n",
    "print(f'shape: {str(len(dls.valid.dataset)):10}   bs: {xb.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 11.1 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 90.7 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.906288</td>\n",
       "      <td>1.125256</td>\n",
       "      <td>0.142909</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.756288</td>\n",
       "      <td>1.085418</td>\n",
       "      <td>0.150437</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.651563</td>\n",
       "      <td>0.937805</td>\n",
       "      <td>0.577465</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.578194</td>\n",
       "      <td>0.720791</td>\n",
       "      <td>0.824794</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.519667</td>\n",
       "      <td>0.510451</td>\n",
       "      <td>0.834628</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.472573</td>\n",
       "      <td>0.458159</td>\n",
       "      <td>0.851627</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.431256</td>\n",
       "      <td>0.848069</td>\n",
       "      <td>0.436255</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.393158</td>\n",
       "      <td>0.351774</td>\n",
       "      <td>0.855877</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.356461</td>\n",
       "      <td>0.721449</td>\n",
       "      <td>0.856241</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.322515</td>\n",
       "      <td>0.195769</td>\n",
       "      <td>0.962118</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.292498</td>\n",
       "      <td>1.183956</td>\n",
       "      <td>0.556217</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.267045</td>\n",
       "      <td>0.333835</td>\n",
       "      <td>0.856605</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.244180</td>\n",
       "      <td>0.804484</td>\n",
       "      <td>0.856605</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.226204</td>\n",
       "      <td>0.770419</td>\n",
       "      <td>0.643759</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.208385</td>\n",
       "      <td>0.236219</td>\n",
       "      <td>0.899830</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.193575</td>\n",
       "      <td>0.372455</td>\n",
       "      <td>0.857576</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.179406</td>\n",
       "      <td>0.104066</td>\n",
       "      <td>0.973531</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.165367</td>\n",
       "      <td>0.105666</td>\n",
       "      <td>0.976445</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.153867</td>\n",
       "      <td>0.107255</td>\n",
       "      <td>0.975352</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.143486</td>\n",
       "      <td>0.118437</td>\n",
       "      <td>0.971467</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.135113</td>\n",
       "      <td>0.107142</td>\n",
       "      <td>0.976081</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.126345</td>\n",
       "      <td>0.093578</td>\n",
       "      <td>0.977052</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.119094</td>\n",
       "      <td>0.089880</td>\n",
       "      <td>0.978630</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.112917</td>\n",
       "      <td>0.088754</td>\n",
       "      <td>0.978509</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.108490</td>\n",
       "      <td>0.088399</td>\n",
       "      <td>0.978388</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34.914013624191284\n"
     ]
    }
   ],
   "source": [
    "model = InceptionTime(X_in_memory.shape[-2], len(np.unique(y_in_memory)))\n",
    "learn = Learner(dls, model, loss_func=nn.CrossEntropyLoss(), metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is definitely an improvement in terms of speed.\n",
    "\n",
    "It is now better than fastai v1! "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NumpyDatasets & NumpyDataLoaders 🤩"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far we we've seen fastai v2 is very flexible and easy to use, but it's slow compared to v1 (in this example the Datablock API was 65% slower). \n",
    "\n",
    "There are at least 3 major differences between vision and time series - TS- (and numpy based data in general) that we can leverage to improve performance: \n",
    "\n",
    "1. Vision tipically requires some item preprocessing that is sometimes random. For example, when you randomly crop an image. Each time it'll return a different value. However, with time series, most item transforms are **deterministic** (actually most impact the label only).\n",
    "\n",
    "2. In vision problems, you usually derive the image and label from a single item (path). In TS problems, it's common to have data already **split between X and y**. It doesn't make much sense to have data already split (into X and y) to merge them in a single item and process them together. \n",
    "\n",
    "3. In vision problems, you can only create a batch processing one image at a time. However with numpy datasets, you can create a batch **processing all batch items** at the same time, just by slicing an array/ tensor, which is much faster.\n",
    "\n",
    "Based on these ideas, we could modify datasets and dataloader and:\n",
    "\n",
    "1. **Preprocess item tfms in place** during datasets initialization, and thus save this time in every epoch\n",
    "\n",
    "2. **Apply the tfms independently to the inputs (X) and labels (y)**. The output of this process 2 arrays or tensors that can be easily sliced. Slicing is a much faster operation than applying a transform.\n",
    "\n",
    "3. Remove the collate function, and instead **slice using all indices at the same time**. Then we can cast the output to the desired subclasses.\n",
    "\n",
    "To test this approach, I've created a NumpyDatasets and NumpyDataLoader that leverage the characteristics of numpy-based datasets.\n",
    "\n",
    "BTW, something important as well, is that fastai v2 design allows the use of larger than RAM datasets, as data can be sliced directly from disk before loading in memory. If you want to learn more about the usage of np.memmap you may want to see nb 00."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use inplace=True whenever you want to speed up training **and**:\n",
    "\n",
    "* you are **not using any tfms, or**\n",
    "* if you are using tfms, **transformed X (and y) both fit in memory**\n",
    "\n",
    "In any inplace won't be effective for items of type np.memmap (to avoid trying to load in memory larger that RAM datasets).\n",
    "In many time series problems, X transforms can be applied after a batch has been created. In all this cases, you can use inplace=True.\n",
    "\n",
    "Inplace=true only impact item transforms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(TSTensor(vars:1, len:1024), TensorCategory(2))\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, tfms=tfms, splits=splits, inplace=True)\n",
    "print(dsets[0])\n",
    "show_at(dsets, 0);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(TSTensor(vars:1, len:1024), TensorCategory(2))\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, tfms=tfms, splits=splits, inplace=True)\n",
    "print(dsets[0])\n",
    "show_at(dsets, 0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have test data, you can just do this: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(vars:1, len:1024), TensorCategory(2))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_ds = dsets.add_test(X_in_memory, y_in_memory)\n",
    "test_ds[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create dataloaders, you just need this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:64, vars:1, len:1024),\n",
       " TensorCategory([1, 0, 1, 2, 2, 2, 2, 1, 0, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 0,\n",
       "         0, 0, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1, 0, 2, 1, 2, 2, 2, 2, 2, 0, 0, 0,\n",
       "         0, 2, 2, 2, 1, 1, 0, 0, 2, 0, 0, 0, 2, 2, 1, 1], device='cuda:0'))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)\n",
    "b = next(iter(dls.train))\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dls.train.show_batch(sharey=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now establish another benchmark. \n",
    "\n",
    "If we think of it, the fastest and simplest way to create a batch to be used in fastai v2 would be to:\n",
    "\n",
    "1. split the X and y between train and valid. This can be done at initialization. \n",
    "\n",
    "2. Slice the data based on random idx, cast the outputs to the expected classes, and create a tuple. \n",
    "\n",
    "This process takes about 200 µs in my machine. So it's very fast."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:128, vars:1, len:1024),\n",
       " TensorCategory([3, 3, 3, 2, 3, 1, 3, 1, 2, 3, 2, 2, 3, 2, 2, 3, 2, 1, 3, 3, 2, 3, 1, 2,\n",
       "         1, 3, 3, 2, 2, 3, 2, 2, 3, 3, 1, 2, 3, 3, 3, 3, 3, 3, 3, 2, 1, 3, 1, 3,\n",
       "         3, 2, 3, 3, 3, 3, 2, 1, 1, 3, 3, 1, 1, 2, 3, 3, 2, 3, 3, 2, 3, 2, 3, 2,\n",
       "         3, 3, 1, 3, 3, 3, 1, 2, 3, 1, 1, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 1, 2, 1,\n",
       "         3, 3, 3, 3, 1, 3, 2, 3, 3, 1, 3, 3, 3, 2, 2, 3, 3, 3, 2, 3, 3, 3, 3, 3,\n",
       "         2, 2, 1, 3, 3, 1, 1, 3]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_val = X_in_memory[splits[1]]\n",
    "y_val = y_in_memory[splits[1]].astype(int)\n",
    "tuple((TSTensor(X_val[valid_idx]), TensorCategory(y_val[valid_idx])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 loops, best of 3: 252 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit tuple((TSTensor(X_val[valid_idx]), TensorCategory(y_val[valid_idx])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see how does this compare to NumpyDatasets when tfms are not preprocessed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preprocess = False\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, sel_vars=None, sel_steps=None, tfms=tfms, splits=splits, inplace=False)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 17.4 ms per loop\n"
     ]
    }
   ],
   "source": [
    "valid_ds = dsets.valid\n",
    "%timeit valid_ds[valid_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 137 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 1.11 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see how is performance when data is preprocessed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preprocess = True\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, sel_vars=None, sel_steps=None, tfms=tfms, splits=splits, inplace=True)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 loops, best of 3: 373 µs per loop\n"
     ]
    }
   ],
   "source": [
    "valid_ds = dsets.valid\n",
    "%timeit valid_ds[valid_idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "😲 Wow! This is superfast! Since we only perform slicing and casting at batch creation time performance is excellent. And it's much faster than when inplace=False. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 11.7 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 38.9 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "🙃 This is even faster than the simple Pytorch dataloader, and much more flexible and with many additional benefits ❣️"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now measure the timing with data on-disk instead of in memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preprocess = True\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_on_disk, y_on_disk, sel_vars=None, sel_steps=None, tfms=tfms, splits=splits, inplace=True)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 loops, best of 3: 995 µs per loop\n"
     ]
    }
   ],
   "source": [
    "valid_ds = dsets.valid\n",
    "%timeit valid_ds[valid_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 15.8 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 89.1 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit cycle_dl(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "⚠️ There's a delay in batch creation when data is on disk, but it's not too bad. It shouldn't have much impact during training!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "Let's now compare the time to train the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.871196</td>\n",
       "      <td>1.050336</td>\n",
       "      <td>0.555002</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.677088</td>\n",
       "      <td>0.725681</td>\n",
       "      <td>0.840578</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.564559</td>\n",
       "      <td>0.443161</td>\n",
       "      <td>0.851627</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.477506</td>\n",
       "      <td>0.587827</td>\n",
       "      <td>0.766270</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.413924</td>\n",
       "      <td>0.427131</td>\n",
       "      <td>0.855512</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.358087</td>\n",
       "      <td>0.511020</td>\n",
       "      <td>0.791161</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.315281</td>\n",
       "      <td>0.322901</td>\n",
       "      <td>0.860369</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.272793</td>\n",
       "      <td>0.840861</td>\n",
       "      <td>0.850413</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.231269</td>\n",
       "      <td>0.283237</td>\n",
       "      <td>0.866561</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.202686</td>\n",
       "      <td>0.229069</td>\n",
       "      <td>0.899830</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.177884</td>\n",
       "      <td>0.298516</td>\n",
       "      <td>0.869111</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.157784</td>\n",
       "      <td>0.140561</td>\n",
       "      <td>0.952647</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.143765</td>\n",
       "      <td>0.106549</td>\n",
       "      <td>0.971952</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.129062</td>\n",
       "      <td>0.123349</td>\n",
       "      <td>0.962360</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.120264</td>\n",
       "      <td>0.105879</td>\n",
       "      <td>0.973531</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.110922</td>\n",
       "      <td>0.102213</td>\n",
       "      <td>0.975838</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.103395</td>\n",
       "      <td>0.127863</td>\n",
       "      <td>0.964910</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.093641</td>\n",
       "      <td>0.085765</td>\n",
       "      <td>0.977052</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.087117</td>\n",
       "      <td>0.112581</td>\n",
       "      <td>0.963453</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.081296</td>\n",
       "      <td>0.092354</td>\n",
       "      <td>0.971224</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.076801</td>\n",
       "      <td>0.083777</td>\n",
       "      <td>0.977295</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.072480</td>\n",
       "      <td>0.083031</td>\n",
       "      <td>0.977538</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.068305</td>\n",
       "      <td>0.082199</td>\n",
       "      <td>0.978509</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.065425</td>\n",
       "      <td>0.080154</td>\n",
       "      <td>0.978995</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.062318</td>\n",
       "      <td>0.080165</td>\n",
       "      <td>0.979480</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "69.35110235214233\n"
     ]
    }
   ],
   "source": [
    "# inplace=False, Data in memory\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, tfms=tfms, splits=splits, inplace=False)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)\n",
    "model = InceptionTime(dls.vars, dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "⚠️ This NumpyDataLoader is faster than fastai v1 even when inplace=False. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.859788</td>\n",
       "      <td>1.141613</td>\n",
       "      <td>0.142909</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.672605</td>\n",
       "      <td>0.778233</td>\n",
       "      <td>0.838392</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.561882</td>\n",
       "      <td>0.506079</td>\n",
       "      <td>0.843613</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.475689</td>\n",
       "      <td>0.350775</td>\n",
       "      <td>0.856119</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.407450</td>\n",
       "      <td>0.473229</td>\n",
       "      <td>0.805124</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.348167</td>\n",
       "      <td>0.491218</td>\n",
       "      <td>0.856848</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.296590</td>\n",
       "      <td>0.282388</td>\n",
       "      <td>0.960782</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.258353</td>\n",
       "      <td>0.190181</td>\n",
       "      <td>0.937955</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.225616</td>\n",
       "      <td>0.266344</td>\n",
       "      <td>0.882831</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.195534</td>\n",
       "      <td>0.156973</td>\n",
       "      <td>0.952768</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.169139</td>\n",
       "      <td>0.108428</td>\n",
       "      <td>0.976202</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.150636</td>\n",
       "      <td>0.283206</td>\n",
       "      <td>0.866076</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.135564</td>\n",
       "      <td>0.098282</td>\n",
       "      <td>0.977659</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.124824</td>\n",
       "      <td>0.142225</td>\n",
       "      <td>0.948397</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.113349</td>\n",
       "      <td>0.131180</td>\n",
       "      <td>0.955197</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.104265</td>\n",
       "      <td>0.136469</td>\n",
       "      <td>0.952161</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.094345</td>\n",
       "      <td>0.186378</td>\n",
       "      <td>0.913065</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.087208</td>\n",
       "      <td>0.176859</td>\n",
       "      <td>0.931763</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.083857</td>\n",
       "      <td>0.086399</td>\n",
       "      <td>0.976688</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.077388</td>\n",
       "      <td>0.083182</td>\n",
       "      <td>0.974988</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.071565</td>\n",
       "      <td>0.073528</td>\n",
       "      <td>0.979723</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.065167</td>\n",
       "      <td>0.074118</td>\n",
       "      <td>0.979966</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.061576</td>\n",
       "      <td>0.072702</td>\n",
       "      <td>0.979966</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.059236</td>\n",
       "      <td>0.072196</td>\n",
       "      <td>0.980087</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.056428</td>\n",
       "      <td>0.072092</td>\n",
       "      <td>0.980087</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37.51224160194397\n"
     ]
    }
   ],
   "source": [
    "# inplace=True, Data in memory\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_in_memory, y_in_memory, tfms=tfms, splits=splits, inplace=True)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)\n",
    "model = InceptionTime(dls.vars, dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "🍻 🎉 I think this is a great result. It means that just preprocessing the item transforms can greatly reduce total training time!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.816127</td>\n",
       "      <td>1.107148</td>\n",
       "      <td>0.142909</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.645581</td>\n",
       "      <td>0.778437</td>\n",
       "      <td>0.795532</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.550639</td>\n",
       "      <td>0.416071</td>\n",
       "      <td>0.845192</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.475615</td>\n",
       "      <td>0.398795</td>\n",
       "      <td>0.854420</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.409876</td>\n",
       "      <td>0.994091</td>\n",
       "      <td>0.856727</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.350317</td>\n",
       "      <td>0.450445</td>\n",
       "      <td>0.808645</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.302406</td>\n",
       "      <td>0.463634</td>\n",
       "      <td>0.856969</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.262711</td>\n",
       "      <td>0.392775</td>\n",
       "      <td>0.822365</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.228694</td>\n",
       "      <td>0.214101</td>\n",
       "      <td>0.919378</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.200736</td>\n",
       "      <td>0.211335</td>\n",
       "      <td>0.931035</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.175025</td>\n",
       "      <td>0.397389</td>\n",
       "      <td>0.863283</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.158893</td>\n",
       "      <td>0.273829</td>\n",
       "      <td>0.876518</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.144522</td>\n",
       "      <td>0.150888</td>\n",
       "      <td>0.960539</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.131883</td>\n",
       "      <td>0.413653</td>\n",
       "      <td>0.848834</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.122439</td>\n",
       "      <td>0.198287</td>\n",
       "      <td>0.909058</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.112285</td>\n",
       "      <td>1.697165</td>\n",
       "      <td>0.524405</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.104197</td>\n",
       "      <td>0.179997</td>\n",
       "      <td>0.927756</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.096276</td>\n",
       "      <td>0.196464</td>\n",
       "      <td>0.911972</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.088380</td>\n",
       "      <td>0.089105</td>\n",
       "      <td>0.974866</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.083434</td>\n",
       "      <td>0.088288</td>\n",
       "      <td>0.974381</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.078454</td>\n",
       "      <td>0.083142</td>\n",
       "      <td>0.974745</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.074534</td>\n",
       "      <td>0.076587</td>\n",
       "      <td>0.980087</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.069377</td>\n",
       "      <td>0.076136</td>\n",
       "      <td>0.979480</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.067080</td>\n",
       "      <td>0.076094</td>\n",
       "      <td>0.978995</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.064221</td>\n",
       "      <td>0.074482</td>\n",
       "      <td>0.979237</td>\n",
       "      <td>00:01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "38.174636363983154\n"
     ]
    }
   ],
   "source": [
    "# inplace=True, Data on disk\n",
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X_on_disk, y_on_disk, tfms=tfms, splits=splits, inplace=True)\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], num_workers=0)\n",
    "model = InceptionTime(dls.vars, dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "start = time.time()\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "print(time.time() - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "⚠️ This is also very important, as it means we can now train very large datasets with a good performance without loading data in memory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## End-to-end process with recommended approach 🏁"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's simulate an end-to-end process to confirm everything works as expected.\n",
    "\n",
    "We'll first build the datasets, learner and train a model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset: NATOPS\n",
      "X      : (360, 24, 51)\n",
      "y      : (360,)\n",
      "splits : (#180) [0,1,2,3,4,5,6,7,8,9...] (#180) [180,181,182,183,184,185,186,187,188,189...] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "dsid = 'NATOPS'\n",
    "X, y, splits = get_UCR_data(dsid, parent_dir='./data/UCR/', verbose=True, on_disk=True, return_split=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1.829068</td>\n",
       "      <td>1.785781</td>\n",
       "      <td>0.194444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1.730444</td>\n",
       "      <td>1.779198</td>\n",
       "      <td>0.238889</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1.583259</td>\n",
       "      <td>1.768679</td>\n",
       "      <td>0.311111</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1.416605</td>\n",
       "      <td>1.748989</td>\n",
       "      <td>0.394444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1.257788</td>\n",
       "      <td>1.710756</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1.118741</td>\n",
       "      <td>1.639137</td>\n",
       "      <td>0.483333</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.998573</td>\n",
       "      <td>1.503884</td>\n",
       "      <td>0.577778</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.906833</td>\n",
       "      <td>1.322600</td>\n",
       "      <td>0.694444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.821100</td>\n",
       "      <td>1.103646</td>\n",
       "      <td>0.844444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.746009</td>\n",
       "      <td>1.000164</td>\n",
       "      <td>0.822222</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.681536</td>\n",
       "      <td>0.756199</td>\n",
       "      <td>0.866667</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.633869</td>\n",
       "      <td>0.724606</td>\n",
       "      <td>0.805556</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.587615</td>\n",
       "      <td>0.823699</td>\n",
       "      <td>0.811111</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.547519</td>\n",
       "      <td>0.696016</td>\n",
       "      <td>0.838889</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.513715</td>\n",
       "      <td>0.436792</td>\n",
       "      <td>0.861111</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.477945</td>\n",
       "      <td>0.276360</td>\n",
       "      <td>0.922222</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.447509</td>\n",
       "      <td>0.216558</td>\n",
       "      <td>0.938889</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.419423</td>\n",
       "      <td>0.198063</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.393053</td>\n",
       "      <td>0.177438</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.369931</td>\n",
       "      <td>0.166122</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.347684</td>\n",
       "      <td>0.157131</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.328195</td>\n",
       "      <td>0.152144</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.310152</td>\n",
       "      <td>0.149684</td>\n",
       "      <td>0.938889</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.294158</td>\n",
       "      <td>0.147742</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.278297</td>\n",
       "      <td>0.145306</td>\n",
       "      <td>0.938889</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tfms  = [None, [Categorize()]]\n",
    "dsets = TSDatasets(X, y, tfms=tfms, splits=splits) # inplace=True by default\n",
    "dls   = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128], batch_tfms=[TSStandardize()], num_workers=0)\n",
    "model = InceptionTime(dls.vars, dls.c)\n",
    "learn = Learner(dls, model, metrics=accuracy)\n",
    "learn.fit_one_cycle(25, lr_max=1e-3)\n",
    "learn.recorder.plot_metrics()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's simulate we need to end the working session now but want to continue working with this datasets and learner in the future. \n",
    "\n",
    "To save everything you can use a convenience function I've created that saves the learner with the model, the data and the opt function status: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.save_all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As soon as we've done this, we can end the session, and continue at any time in the future. \n",
    "\n",
    "Let's simulate that we need to end the session now:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "del learn, dsets, dls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next time we go back to work, we'll need to reload the datasets and learner (with the same status we had):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:128, vars:24, len:51),\n",
       " TensorCategory([3, 4, 5, 0, 3, 2, 1, 2, 2, 0, 4, 3, 2, 4, 1, 0, 4, 0, 4, 0, 2, 3, 5, 5,\n",
       "         1, 2, 1, 0, 1, 4, 2, 3, 5, 4, 3, 5, 3, 0, 3, 5, 4, 2, 1, 5, 0, 2, 4, 3,\n",
       "         2, 2, 2, 2, 0, 2, 0, 1, 0, 0, 4, 1, 4, 5, 0, 5, 1, 1, 1, 2, 4, 1, 5, 3,\n",
       "         0, 3, 4, 3, 1, 4, 4, 2, 0, 3, 3, 5, 1, 5, 2, 5, 5, 4, 4, 2, 4, 3, 5, 2,\n",
       "         1, 5, 0, 3, 0, 5, 3, 5, 0, 5, 5, 0, 2, 5, 0, 1, 1, 4, 1, 0, 0, 2, 4, 1,\n",
       "         0, 3, 4, 3, 1, 2, 2, 2]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn = load_learner_all(path='export', dls_fname='dls', model_fname='model', learner_fname='learner', device='cpu')\n",
    "dls = learn.dls\n",
    "first(dls.valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now analyze the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.show_results(sharey=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(tensor([[0.0052, 0.0029, 0.0071, 0.9698, 0.0057, 0.0093],\n",
       "         [0.0066, 0.0082, 0.0037, 0.0090, 0.9603, 0.0122],\n",
       "         [0.0017, 0.0024, 0.0021, 0.0055, 0.0033, 0.9851],\n",
       "         ...,\n",
       "         [0.0040, 0.0049, 0.0017, 0.0055, 0.9799, 0.0041],\n",
       "         [0.0041, 0.0021, 0.0052, 0.9780, 0.0040, 0.0066],\n",
       "         [0.0035, 0.0035, 0.0062, 0.9260, 0.0529, 0.0080]]),\n",
       " TensorCategory([3, 4, 5, 0, 3, 2, 1, 2, 2, 0, 4, 3, 2, 4, 1, 0, 4, 0, 4, 0, 2, 3, 5, 5,\n",
       "         1, 2, 1, 0, 1, 4, 2, 3, 5, 4, 3, 5, 3, 0, 3, 5, 4, 2, 1, 5, 0, 2, 4, 3,\n",
       "         2, 2, 2, 2, 0, 2, 0, 1, 0, 0, 4, 1, 4, 5, 0, 5, 1, 1, 1, 2, 4, 1, 5, 3,\n",
       "         0, 3, 4, 3, 1, 4, 4, 2, 0, 3, 3, 5, 1, 5, 2, 5, 5, 4, 4, 2, 4, 3, 5, 2,\n",
       "         1, 5, 0, 3, 0, 5, 3, 5, 0, 5, 5, 0, 2, 5, 0, 1, 1, 4, 1, 0, 0, 2, 4, 1,\n",
       "         0, 3, 4, 3, 1, 2, 2, 2, 2, 0, 4, 0, 0, 1, 3, 4, 4, 2, 1, 1, 1, 4, 4, 3,\n",
       "         1, 4, 0, 4, 5, 5, 1, 5, 3, 3, 5, 5, 4, 3, 5, 1, 3, 2, 3, 0, 1, 3, 0, 2,\n",
       "         5, 2, 1, 5, 3, 1, 0, 5, 2, 4, 3, 3]),\n",
       " tensor([3, 4, 5, 0, 3, 2, 2, 2, 2, 0, 4, 3, 2, 4, 1, 0, 4, 0, 4, 0, 2, 3, 5, 5,\n",
       "         1, 2, 2, 0, 1, 4, 2, 3, 5, 4, 3, 5, 3, 0, 3, 5, 4, 1, 1, 5, 0, 2, 4, 3,\n",
       "         2, 2, 1, 2, 0, 1, 0, 2, 0, 0, 4, 1, 4, 5, 0, 5, 1, 1, 1, 2, 4, 1, 5, 3,\n",
       "         0, 3, 4, 3, 1, 4, 4, 2, 0, 3, 3, 5, 1, 5, 2, 5, 5, 4, 4, 2, 4, 3, 5, 1,\n",
       "         1, 5, 0, 3, 0, 5, 3, 5, 0, 5, 5, 0, 2, 5, 0, 1, 1, 4, 1, 0, 0, 2, 4, 1,\n",
       "         0, 3, 4, 3, 1, 2, 2, 2, 2, 0, 4, 0, 0, 2, 3, 4, 4, 2, 1, 2, 1, 4, 4, 3,\n",
       "         1, 4, 0, 4, 5, 5, 1, 5, 3, 3, 5, 5, 4, 3, 5, 1, 3, 1, 3, 0, 1, 3, 0, 2,\n",
       "         5, 2, 1, 5, 3, 1, 0, 5, 1, 4, 3, 3]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid_probas, valid_targets, valid_preds = learn.get_preds(dl=dls.valid, with_decoded=True)\n",
    "valid_probas, valid_targets, valid_preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can confirm the learner has the same status it had at the end of training, by confirming the validation accuracy is the same:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorCategory(0.9389)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(valid_targets == valid_preds).float().mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! It's the same. This means we have now the learner at the same point where we left it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "interp = ClassificationInterpretation.from_learner(learn)\n",
    "interp.plot_confusion_matrix()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add additional labeled test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:128, vars:24, len:51),\n",
       " TensorCategory([3, 2, 2, 3, 2, 4, 0, 5, 2, 1, 5, 0, 3, 5, 2, 1, 2, 1, 1, 5, 3, 2, 4, 3,\n",
       "         0, 5, 2, 4, 4, 4, 2, 4, 2, 4, 3, 4, 2, 0, 3, 5, 2, 3, 3, 5, 0, 5, 1, 0,\n",
       "         0, 5, 3, 0, 2, 2, 1, 0, 4, 0, 1, 4, 3, 4, 1, 4, 0, 5, 2, 0, 1, 0, 2, 3,\n",
       "         3, 2, 4, 1, 1, 2, 2, 5, 5, 0, 1, 4, 1, 1, 3, 4, 5, 3, 1, 2, 0, 2, 0, 4,\n",
       "         5, 5, 4, 4, 5, 3, 1, 0, 1, 1, 1, 5, 4, 3, 2, 3, 0, 2, 4, 4, 4, 3, 2, 5,\n",
       "         2, 0, 2, 3, 0, 5, 1, 0]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Labeled test data\n",
    "test_ds = dls.valid.dataset.add_test(X, y)\n",
    "test_dl = dls.valid.new(test_ds)\n",
    "next(iter(test_dl))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(tensor([[3.2659e-03, 1.6339e-03, 4.3155e-03, 9.8212e-01, 3.2800e-03, 5.3898e-03],\n",
       "         [1.1431e-03, 6.2102e-03, 9.8809e-01, 1.5289e-03, 2.4123e-03, 6.1626e-04],\n",
       "         [7.0222e-03, 5.1627e-02, 9.2067e-01, 7.8512e-03, 8.4117e-03, 4.4176e-03],\n",
       "         ...,\n",
       "         [3.9725e-03, 4.8957e-03, 1.6728e-03, 5.4505e-03, 9.7992e-01, 4.0927e-03],\n",
       "         [4.1386e-03, 2.1447e-03, 5.1585e-03, 9.7796e-01, 3.9735e-03, 6.6209e-03],\n",
       "         [3.4568e-03, 3.4819e-03, 6.1575e-03, 9.2598e-01, 5.2933e-02, 7.9918e-03]]),\n",
       " TensorCategory([3, 2, 2, 3, 2, 4, 0, 5, 2, 1, 5, 0, 3, 5, 2, 1, 2, 1, 1, 5, 3, 2, 4, 3,\n",
       "         0, 5, 2, 4, 4, 4, 2, 4, 2, 4, 3, 4, 2, 0, 3, 5, 2, 3, 3, 5, 0, 5, 1, 0,\n",
       "         0, 5, 3, 0, 2, 2, 1, 0, 4, 0, 1, 4, 3, 4, 1, 4, 0, 5, 2, 0, 1, 0, 2, 3,\n",
       "         3, 2, 4, 1, 1, 2, 2, 5, 5, 0, 1, 4, 1, 1, 3, 4, 5, 3, 1, 2, 0, 2, 0, 4,\n",
       "         5, 5, 4, 4, 5, 3, 1, 0, 1, 1, 1, 5, 4, 3, 2, 3, 0, 2, 4, 4, 4, 3, 2, 5,\n",
       "         2, 0, 2, 3, 0, 5, 1, 0, 5, 3, 0, 1, 4, 5, 5, 0, 5, 3, 5, 1, 0, 0, 0, 3,\n",
       "         0, 5, 5, 2, 1, 5, 5, 2, 4, 4, 0, 1, 1, 4, 1, 2, 2, 4, 1, 3, 5, 3, 4, 1,\n",
       "         1, 4, 3, 0, 5, 1, 3, 3, 4, 0, 3, 3, 3, 4, 5, 0, 3, 2, 1, 2, 2, 0, 4, 3,\n",
       "         2, 4, 1, 0, 4, 0, 4, 0, 2, 3, 5, 5, 1, 2, 1, 0, 1, 4, 2, 3, 5, 4, 3, 5,\n",
       "         3, 0, 3, 5, 4, 2, 1, 5, 0, 2, 4, 3, 2, 2, 2, 2, 0, 2, 0, 1, 0, 0, 4, 1,\n",
       "         4, 5, 0, 5, 1, 1, 1, 2, 4, 1, 5, 3, 0, 3, 4, 3, 1, 4, 4, 2, 0, 3, 3, 5,\n",
       "         1, 5, 2, 5, 5, 4, 4, 2, 4, 3, 5, 2, 1, 5, 0, 3, 0, 5, 3, 5, 0, 5, 5, 0,\n",
       "         2, 5, 0, 1, 1, 4, 1, 0, 0, 2, 4, 1, 0, 3, 4, 3, 1, 2, 2, 2, 2, 0, 4, 0,\n",
       "         0, 1, 3, 4, 4, 2, 1, 1, 1, 4, 4, 3, 1, 4, 0, 4, 5, 5, 1, 5, 3, 3, 5, 5,\n",
       "         4, 3, 5, 1, 3, 2, 3, 0, 1, 3, 0, 2, 5, 2, 1, 5, 3, 1, 0, 5, 2, 4, 3, 3]),\n",
       " tensor([3, 2, 2, 3, 2, 4, 0, 5, 2, 1, 5, 0, 3, 5, 2, 1, 2, 1, 1, 5, 3, 2, 4, 3,\n",
       "         0, 5, 2, 4, 4, 4, 2, 4, 2, 4, 3, 4, 2, 0, 3, 5, 2, 3, 3, 5, 0, 5, 1, 0,\n",
       "         0, 5, 3, 0, 2, 2, 1, 0, 4, 0, 1, 4, 3, 4, 1, 4, 0, 5, 2, 0, 1, 0, 2, 3,\n",
       "         3, 2, 4, 1, 1, 2, 2, 5, 5, 0, 1, 4, 1, 1, 3, 4, 5, 3, 1, 2, 0, 2, 0, 4,\n",
       "         5, 5, 4, 4, 5, 3, 1, 0, 1, 1, 1, 5, 4, 3, 2, 3, 0, 2, 4, 4, 4, 3, 2, 5,\n",
       "         2, 0, 2, 3, 0, 5, 1, 0, 5, 3, 0, 1, 4, 5, 5, 0, 5, 3, 5, 1, 0, 0, 0, 3,\n",
       "         0, 5, 5, 2, 1, 5, 5, 2, 4, 4, 0, 1, 1, 4, 1, 2, 2, 4, 1, 3, 5, 3, 4, 1,\n",
       "         1, 4, 3, 0, 5, 1, 3, 3, 4, 0, 3, 3, 3, 4, 5, 0, 3, 2, 2, 2, 2, 0, 4, 3,\n",
       "         2, 4, 1, 0, 4, 0, 4, 0, 2, 3, 5, 5, 1, 2, 2, 0, 1, 4, 2, 3, 5, 4, 3, 5,\n",
       "         3, 0, 3, 5, 4, 1, 1, 5, 0, 2, 4, 3, 2, 2, 1, 2, 0, 1, 0, 2, 0, 0, 4, 1,\n",
       "         4, 5, 0, 5, 1, 1, 1, 2, 4, 1, 5, 3, 0, 3, 4, 3, 1, 4, 4, 2, 0, 3, 3, 5,\n",
       "         1, 5, 2, 5, 5, 4, 4, 2, 4, 3, 5, 1, 1, 5, 0, 3, 0, 5, 3, 5, 0, 5, 5, 0,\n",
       "         2, 5, 0, 1, 1, 4, 1, 0, 0, 2, 4, 1, 0, 3, 4, 3, 1, 2, 2, 2, 2, 0, 4, 0,\n",
       "         0, 2, 3, 4, 4, 2, 1, 2, 1, 4, 4, 3, 1, 4, 0, 4, 5, 5, 1, 5, 3, 3, 5, 5,\n",
       "         4, 3, 5, 1, 3, 1, 3, 0, 1, 3, 0, 2, 5, 2, 1, 5, 3, 1, 0, 5, 1, 4, 3, 3]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_probas, test_targets, test_preds = learn.get_preds(dl=test_dl, with_decoded=True, save_preds=None, save_targs=None)\n",
    "test_probas, test_targets, test_preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add additional unlabeled test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TSTensor(samples:128, vars:24, len:51),)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unlabeled test data\n",
    "test_ds = dls.dataset.add_test(X)\n",
    "test_dl = dls.valid.new(test_ds)\n",
    "next(iter(test_dl))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "tensor([[3.2659e-03, 1.6339e-03, 4.3155e-03, 9.8212e-01, 3.2800e-03, 5.3898e-03],\n",
       "        [1.1431e-03, 6.2102e-03, 9.8809e-01, 1.5289e-03, 2.4123e-03, 6.1626e-04],\n",
       "        [7.0222e-03, 5.1627e-02, 9.2067e-01, 7.8512e-03, 8.4117e-03, 4.4176e-03],\n",
       "        ...,\n",
       "        [3.9725e-03, 4.8957e-03, 1.6728e-03, 5.4505e-03, 9.7992e-01, 4.0927e-03],\n",
       "        [4.1386e-03, 2.1447e-03, 5.1585e-03, 9.7796e-01, 3.9735e-03, 6.6209e-03],\n",
       "        [3.4568e-03, 3.4819e-03, 6.1575e-03, 9.2598e-01, 5.2933e-02, 7.9918e-03]])"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_probas, *_ = learn.get_preds(dl=test_dl, save_preds=None)\n",
    "test_probas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions ✅"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In summary, we've seen how we can now enjoy all the benefits of v2 when using numpy arrays with a simple scikit-learn-like API, that is much faster than v1. \n",
    "\n",
    "The key benefits are: \n",
    "\n",
    "* We can easily use numpy arrays (or anything that can be converted into np arrays). For example, this can be used for **univariate and multivariate time series**.\n",
    "* Easy to use scikit-learn type of API (X, (y))\n",
    "* We can use both **labeled and unlabeled datasets**\n",
    "* We can also use **larger than RAM datasets**, keeping data on disk (using np.memmap -see nb 00 for more details-).\n",
    "* Use item and batch tfms\n",
    "* Show batch method after tfms have been applied\n",
    "* Show results after training\n",
    "* **Easily export** the model to continue at a later time.\n",
    "* With NumpyDatasets + NumpyDataLoaders batch creation is **25+x faster than fastai v1** and **100+ times faster than vanilla fastai v2** (for numpy arrays).\n",
    "* This results in **2.5-3x faster training** than fastai v1 and **4-5x faster than vanilla fastai v2** (for numpy arrays)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
